Is Home Dialysis the Way Forward for Medicare? Assessing Potential Cost Savings Associated with Peritoneal Dialysis
Authors: Sri Lekha Tummalapalli, Eugene Lin
Journal: Journal of the American Society of Nephrology (2022)

Amid the Advancing American Kidney Health initiatives and the ESRD Treatment Choices Model, efforts to increase peritoneal dialysis (PD) utilization are accelerating. In this issue of JASN, Kaplan et al.1 analyze the differences in Medicare spending on PD versus in-center hemodialysis (HD). The authors analyze expenditure data from the United States Renal Data System (USRDS) for patients with incident ESKD aged ≥67 years with Medicare Parts A, B, and D who initiated PD or HD. During the time period analyzed (2008–2015), the ESRD Prospective Payment System (ESRD PPS) was implemented, and PD utilization among patients with incident ESKD increased from 5.9% to 9.6%.2 To conduct a fair comparison between PD and HD, the authors constructed propensity scores from sociodemographics and comorbidities. They then matched patients with a similar propensity to initiate PD and compared their differences in total Medicare spending, outpatient dialysis spending (intravenous drugs and other dialysis), and nondialysis spending (acute care, rehabilitation care, other nondialysis, and dialysis access). Average expenditures were $108,656/yr for patients on HD and $91,716/yr for matched patients on PD, with differences primarily driven by rehabilitation, dialysis access, and other nondialysis spending. Cost savings associated with PD were concentrated in the first year of incident ESKD (adjusted HD-PD payment ratio, 1.18; 95% confidence interval [95% CI], 1.15 to 1.20); PD was associated with higher costs in subsequent years. Despite increases in PD utilization between 2008 and 2015, cost differences between PD and HD remained stable over time. Comparative studies between PD and HD are frequently hampered by confounding factors. For example, patients with higher socioeconomic status, better family support, and better access to predialysis nephrology care are more likely to initiate home modalities and simultaneously, have lower health care spending.3 A strength of the analysis of Kaplan et al.1 is their propensity score matching approach that incorporated a rich set of demographic and clinical variables, including predialysis nephrology visits, and social factors, like urbanicity, Medicaid, and low-income subsidy enrollment. Still, residual confounding could remain. The authors could not adjust for individual-level social determinants of health, functional status, or self-management behaviors, which are not present in USRDS data. These factors are important to consider because frailty is associated with more HD use and costly complications.4 Similarly, adherence to medications and care plans could affect dialysis modality choice as well as health care spending. Another analysis by Lin et al.5 used a quasiexperimental approach in a different patient population—uninsured patients with incident ESKD predominantly aged ≤65. This study simulated a randomized trial to address unobserved confounding and found no statistically significant difference in Medicare expenditures in months 7–12 after dialysis initiation. The cheaper costs associated with PD in the study of Kaplan et al.1 could be due to the older population, residual confounding (e.g., healthier, wealthier patients selecting PD), or both. Nonetheless, results from Kaplan et al.1 illuminate potential mechanisms by which PD may confer cost savings. In adjusted analyses, dialysis access costs were 12% higher in HD versus PD, suggesting more frequent HD access complications, such as arteriovenous fistula/graft thromboses and HD catheter-associated infections, compared with PD catheter malfunction. Rehabilitation expenditures were 35% higher in HD versus PD, suggesting poorer functional status of patients on HD and more inpatient hospitalizations requiring postacute care. Other nondialysis spending was 34% higher in HD versus PD, which may reflect greater pharmaceutical spending, emergency department visits, observation stays, and/or ambulatory care. Acute care spending—the most costly nondialysis category—was higher for patients on HD ($38,793) versus matched patients on PD ($33,520) but not statistically different in analyses adjusted for hemoglobin, albumin, body mass index, and predialysis spending. The economic analysis of PD and HD by Kaplan et al.1 has several clinical and policy implications. First, clinicians and health systems should leverage this detailed analysis to identify opportunities to reduce overall health care spending for both patients on PD and patients on HD. As clinicians and dialysis organizations bear more financial risk through value-based care models (e.g., Comprehensive Kidney Care Contracting) and capitated arrangements with Medicare Advantage plans, there is intensified interest to lower total costs of care through population-based interventions. Notably, a substantial portion of PD cost savings was concentrated in the first 90 days of dialysis initiation. When this initial period was excluded, cost differences were attenuated from an HD-PD payment ratio of 1.11 (95% CI, 1.09 to 1.13) to 1.04 (95% CI, 1.00 to 1.09). Because patients who choose PD often do not "crash start," initiating dialysis on an outpatient basis could narrow much of the cost difference between PD and HD.6 Second, these results are promising because cost savings associated with PD were maintained during a time when PD utilization nearly doubled. Reassuringly, technique failure rates (conversion from PD to in-center HD) are largely stable, and hospitalizations for catheter complications and peritonitis are declining according to the latest USRDS annual report.2 Continued surveillance of home dialysis complications and health care costs is critical under the ESRD Treatment Choices Model, which financially incentivizes home dialysis, but thus far, clinical and economic indicators are pointing in the right direction. Notably, the authors did not analyze younger age groups and patients without Part D enrollment. Understanding whether PD savings generalize to these patients is important because the majority of patients on PD are under age 65 and only 70% have Part D coverage.2 Third, researchers and policy makers should remain attuned to other cost perspectives, particularly those borne by patients and caregivers.7 Future research should focus on quantifying home dialysis costs associated with uncompensated labor, utilities, and home renovations. Such research could inform whether potential cost savings from increased PD should be allocated toward new policies supporting patients performing PD. For instance, direct cash payments and staff-assisted home dialysis might yield societal benefits, including improved quality of life, self-efficacy, and the ability to maintain employment while on home dialysis.8 In summary, Kaplan et al.1 find lower expenditures in patients on PD compared with patients on HD spanning the ESRD PPS transition. These findings are reassuring in that promoting more home dialysis might reduce ESKD spending. Still, because these findings are observational and limited to an older incident population, researchers and policy makers should conduct additional analyses to ensure that cost savings are realized. Disclosures E. Lin receives consulting income from Acumen, LLC, a federal contractor. E. Lin also reports advisory or leadership roles with the American Journal of Kidney Diseases Editorial Board, the Kidney News Editorial Board, the National Kidney Foundation Scientific Advisory Board, the Nephrology News and Issues Editorial Advisory Board, and the Seminars in Dialysis Editorial Board. S.L. Tummalapalli received research funding from Scanwell Health and consulting fees from Bayer AG unrelated to the submitted work. Funding E. Lin receives salary support from National Institute of Diabetes and Digestive and Kidney Diseases grants K08 DK118213 and R03 DK131239. He also receives support from the American Society of Nephrology's KidneyCure and the ASN Foundation for Kidney Research Carl W. Gottschalk Research Scholar Grant. S.L. Tummalapalli is supported by funding from Agency for Healthcare Research and Quality grant K08HS028684.